TRUST AND ADOPTION OF ROBO- ADVISORS VS. HUMAN ADVISORS IN PORTFOLIO MANAGEMENT: AN ANALYTICAL STUDY

Abstract

As innovative technologies, the evolution of online behavior, and advancements in investor expectations shape our industry, the financial advisory space is undergoing fundamental changes. For many years, human advisors were the cornerstone of financial advice - providing meaningful personalized advice through human connection and emotional support. Now, with the introduction of automated platforms - otherwise known as robo-advisors - the delivery of financial advice has never been cheaper and more accessible. This leads to the question of do investors prefer technology, stay with human advisors, or decide on a hybrid model of both? With the growing interest in hybrid advisory models, the present study, "Trust and Adoption of Robo-Advisors vs. Human Advisors in Portfolio Management: An Analytical Research Study" examines the aspects of investor trust, preferences, and behaviors. The study uses a quantitative method to assess how demographics affect trust in robo- advisors and human advisors. It focuses on factors like age, gender, income, education, experience, and investment goals. A structured questionnaire was created and shared with investors in India. A total of 190 valid responses were collected. The data was examined using cross-tabulation, chi-square tests, and correlation analysis. Eight hypotheses were tested to understand how investor characteristics relate to their trust and behaviour toward different advisory models. The findings show clear differences in investor preferences based on demographics. Male investors preferred equities and cryptocurrencies, showing more risk-taking behavior. Female investors leaned toward safer options like fixed deposits and were more cautious. This reflects gender-based differences in risk appetite and advisory choices. Income also influenced behavior. High-income groups were more likely to use robo- advisors, likely due to better digital skills and risk tolerance. Educated investors were more aware of and open to robo-advisory services, showing that education supports tech adoption. Experienced investors were more comfortable with automated tools. In contrast, new investors preferred human advisors for support and reassurance. vi Younger investors (under 35) trusted robo-advisors more. They were tech-savvy and liked low-cost, automated services. Older investors preferred human advisors for personal interaction and guidance. This highlights a generational gap in trust and comfort with technology. Despite increasing robo-advisory penetration, trust is the biggest obstacle. Most of the respondents had issues with the absence of human empathy, contextual awareness, and emotional intelligence in robo-advisory systems. Investors who had long-term planning, retirement, or sophisticated portfolios as their priorities still preferred human advisers because of the all-encompassing advice and responsibility they provide. Robo-advisors were, however, valued for their reduced costs, 24/7 availability, and data-based suggestions, particularly for simple investment requirements or portfolio rebalancing. During these discoveries, there was a strong leaning towards hybrid models—a model that combines the efficiency of robo-advisors with the human touch of financial professionals. Hybrid advisory platforms can leverage the strengths of both models: automation for data analysis, portfolio optimization, and scalability; and human advisors for relationship building, emotional support, and customized planning. Many investors, especially those entering higher-income brackets or preparing for major life events, were looking for a hybrid model that provides balanced, stable, and responsive financial advice. The study shows that the future of financial advice is not about choosing between human or automated systems. Instead, the best approach combines both in a hybrid model. This model uses technology for tasks like investment selection and portfolio monitoring, while human advisors handle complex issues such as tax planning, strategic decisions, and coaching clients through market changes. The hybrid model helps overcome the weaknesses of using only robo-advisors or only human advisors. Automation brings efficiency, lower costs, and 24/7 access. Human advisors add personal service, emotional support, and expert judgment for complicated needs. This combination leads to a better client experience and more tailored advice5. Financial institutions and fintech companies can use these findings to design services for different types of clients. Younger, tech-savvy investors may prefer digital tools, vii but they can still get human help for special questions or reviews. Older clients can gradually move to digital platforms while keeping strong relationships with their advisors. This flexible approach meets the needs of a wider range of investors and helps firms reach more clients, improve efficiency, and reduce costs. In summary, the hybrid model blends technology and human expertise. It gives clients both convenience and personal attention, making financial advice more accessible and effective for everyone The study further points to some key considerations for policymakers and industry regulators. With the growing relevance of digital advisory services, there will be a need to prioritise data privacy, transparency, algorithmic accountability, and investor education. There will be a need for clear regulatory frameworks regarding hybrid advisory practices, fiduciary obligations, and disclosure. standards. Investor trust can be enhanced not only through tailored services but also through the enforcement of ethical practices, full-service customer support, and user-friendly platforms. In conclusion, this research makes a valuable contribution to the dynamic portfolio management field by demonstrating that investor trust, preference, and adoption are highly contextual and multifaceted. The hybrid advisory model is the most viable and sustainable solution at present, and it can potentially address investor needs in all demographics and expectations. By adopting the model, the financial advisory profession can achieve broader reach, greater trust, and higher satisfaction in a more digital and complex investment environment.